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Machine Learning Design Patterns: Solutions to Common Challenges in Data Preparation, Model Building, and MLOps (Paperback)
By:
Valliappa Lakshmanan
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Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications (Paperback)
By:
Chip Huyen
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Introducing MLOps: How to Scale Machine Learning in the Enterprise (Paperback)
By:
Mark Treveil
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Practical MLOps: Operationalizing Machine Learning Models (Paperback)
By:
Noah Gift
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Building Machine Learning Powered Applications: Going from Idea to Product (Paperback)
By:
Emmanuel Ameisen
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AI Engineering: Building Applications with Foundation Models (Paperback)
By:
Chip Huyen
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Reliable Machine Learning: Applying SRE Principles to ML in Production (Paperback)
By:
Cathy Chen
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Effective Data Science Infrastructure: How to make data scientists productive (Paperback)
By:
Ville Tuulos
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Machine Learning Engineering in Action (Kindle Edition)
By:
Ben Wilson
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Building Machine Learning Pipelines: Automating Model Life Cycles with TensorFlow (Paperback)
By:
Hannes Hapke
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Kubeflow for Machine Learning: From Lab to Production (Paperback)
By:
Trevor Grant
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Designing Data-Intensive Applications (ebook)
By:
Martin Kleppmann
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Shipping Machine Learning Systems: A Practical Guide to Building, Deploying, and Scaling in Production (Paperback)
By:
El-Geish
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Machine Learning System Design: With end-to-end examples (Hardcover)
By:
Valerii Babushkin
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Implementing MLOps in the Enterprise: A Production-First Approach (Paperback)
By:
Yaron Haviv
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Machine Learning Engineering with Python: Manage the lifecycle of machine learning models using MLOps with practical examples (Kindle Edition)
By:
Andrew McMahon
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Data Science on AWS (ebook)
By:
Chris Fregly
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Distributed Machine Learning Patterns (Paperback)
By:
Yuan Tang
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MLOps Engineering at Scale (Kindle Edition)
By:
Carl Osipov
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Machine Learning Engineering with Python: Manage the production life cycle of machine learning models using MLOps with practical examples (Paperback)
By:
Andrew P. McMahon
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Data Science in Production: Building Scalable Model Pipelines with Python (Kindle Edition)
By:
Ben Weber
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Beginning MLOps with MLFlow: Deploy Models in AWS SageMaker, Google Cloud, and Microsoft Azure (Paperback)
By:
Sridhar Alla
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Machine Learning Platform Engineering: Build an internal developer platform for ML and AI systems (From Scratch)
By:
Benjamin Tan Wei Hao
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Docker Deep Dive: Zero to Docker in a single book (Kindle Edition)
By:
Nigel Poulton
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PRODUCTION READY DATA SCIENCE: From Prototyping to Production with Python (Kindle Edition)
By:
Khuyen Tran
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LLM Engineer's Handbook: Master the art of engineering large language models from concept to production (Kindle Edition)
By:
Paul Iusztin
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Optimizing Generative AI Workloads for Sustainability: Balancing Performance and Environmental Impact in Generative AI (Kindle Edition)
By:
Ishneet Kaur Dua
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Natural Language Processing with Python: Analyzing Text with the Natural Language Toolkit (Paperback)
By:
Steven Bird
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Pragmatic AI: An Introduction to Cloud-Based Machine Learning (Addison Wesley Data & Analytics)
By:
Noah Gift
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RAG-Driven Generative AI: Build custom retrieval augmented generation pipelines with LlamaIndex, Deep Lake, and Pinecone (Paperback)
By:
Denis Rothman
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The KCNA Book: Kubernetes and Cloud Native Associate (Mastering Kubernetes Book 3)
By:
Nigel Poulton
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The AI Playbook: Mastering the Rare Art of Machine Learning Deployment (Hardcover)
By:
Eric Siegel
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Quick Start Kubernetes (Kindle Edition)
By:
Nigel Poulton
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Practical Machine Learning on Databricks: Seamlessly transition ML models and MLOps on Databricks (Kindle Edition)
By:
Debu Sinha
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Mining of Massive Datasets (Hardcover)
By:
Jure Leskovec
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Machine Learning with Python Cookbook: Practical Solutions from Preprocessing to Deep Learning (Paperback)
By:
Kyle Gallatin
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Cost-Effective Data Pipelines: Balancing Trade-Offs When Developing Pipelines in the Cloud (Paperback)
By:
Sev Leonard
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Scaling Machine Learning with Spark: Distributed ML with MLlib, TensorFlow, and PyTorch (Paperback)
By:
Adi Polak
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Not with a Bug, But with a Sticker: Attacks on Machine Learning Systems and What To Do About Them (Hardcover)
By:
Ram Shankar Siva Kumar
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Foundations for Architecting Data Solutions: Managing Successful Data Projects (Paperback)
By:
Ted Malaska
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The DataOps Cookbook (ebook)
By:
Christopher Bergh
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The Kubernetes Book (Paperback)
By:
Nigel Poulton
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What Is MLOps? (ebook)
By:
Mark Treveil
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Agile Data Science 2.0: Building Full-Stack Data Analytics Applications with Spark (Paperback)
By:
Russell Jurney
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Data Quality Fundamentals (Unknown Binding)
By:
Barr Moses
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Deep Learning in Production (Paperback)
By:
Sergios Karagiannakos
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Data Pipelines Pocket Reference: Moving and Processing Data for Analytics (Paperback)
By:
James Densmore
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Practical Dataops: Delivering Agile Data Science at Scale (Paperback)
By:
Harvinder Atwal